A1116
Title: On robust testing for trend
Authors: Anton Skrobotov - Russian Presidential Academy of National Economy and Public Administration and SPBU (Russia) [presenting]
Abstract: A simple approach is provided for robust testing for the trend function in the time series under uncertainty over the order of integration of the error term. The proposed approach relies on the asymptotic normality of the trend coefficient estimator and utilises a $t$-statistic approach based on splitting the sample. The Monte-Carlo results demonstrate that the approach has the correct finite sample size and favorable finite sample power properties for all data generating processes considered. The proposed approach is robust to very general assumptions on the error term including various forms of non-stationary volatility and heavy tails.
